Triple
T26100466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexican telephone numbering plan |
E658384
|
entity |
| Predicate | usesNationalSignificantNumberLength |
P110644
|
FINISHED |
| Object | 10 digits |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 10 digits | Statement: [Mexican telephone numbering plan, usesNationalSignificantNumberLength, 10 digits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNationalSignificantNumberLength Context triple: [Mexican telephone numbering plan, usesNationalSignificantNumberLength, 10 digits]
-
A.
maximumNationalNumberLength
chosen
Indicates the greatest number of digits allowed in a national (domestic) phone number for a given country or numbering plan.
-
B.
nationalPrefixForDomesticCalls
Indicates the dialing prefix that must be used when making domestic telephone calls within a given country or numbering plan.
-
C.
areaCodeLength
Indicates the number of digits or characters that make up a given area code.
-
D.
countryCodeLength
Indicates the number of characters that a given country code consists of.
-
E.
usesVariableLengthAreaCodes
Indicates that the telephone numbering plan in question employs area codes whose lengths are not fixed but can vary.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ee5bc09c288190bc42a11972841383 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6073a39408190994ac1c8983a7c0b |
completed | May 2, 2026, 2:16 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 7:54 p.m.